Imprint Apparatus Drop Recipe Determination via Iterative Curing

The system performs preliminary actions by predicting the pattern quality before actually executing the imprint process. The prediction unit calculates quality metrics based on the drop recipe and pattern data, allowing the system to identify problematic recipes without wasting time on actual printing and evaluation cycles.

The invention replaces the mechanical trial-and-error process (actual imprinting and physical pattern evaluation) with an information-based prediction system. The prediction unit uses computational methods to substitute for the physical iteration process, dramatically reducing the time and cost while maintaining optimization effectiveness.

The system implements feedback by using the prediction unit to continuously evaluate the quality of generated drop recipes. The quality determination unit provides feedback signals that guide the generation unit to refine and improve recipes, enabling rapid iteration without physical printing cycles and significantly enhancing productivity while maintaining reliability.

The invention creates virtual copies of the pattern quality evaluation through prediction calculations. Instead of physically printing and evaluating each recipe variant, the system uses computational models to copy the evaluation process, allowing multiple iterations to occur simultaneously and dramatically improving efficiency.